ITBusiness.ca

GestureLogic shines spotlight on Ottawa-area startups

What happens when a university electronics professor wants to use technology to improve his health? In the case of Leonard MacEachern you get one of the most interesting startups to come out of the Ottawa area in quite some time. Not only is MacEachern an associate professor of electronics engineering at Carleton University, he is also the CEO and co-founder of the wearable technology start-up, GestureLogic.

GestureLogic is the result of MacEachern’s long-held desire for a piece of technology that could measure his fitness progress without him needing to be a rocket scientist. Even with his position at the university he knew that the average consumer wanted simplicity and not data that could not be actionable right away.

Which is where the idea for GestureLogic’s first product – LEO – comes from. LEO’s fitness intelligence technology not only measures a user’s bio-signals but it also delivers the information from these signals in simple and actionable insights. See video below:

I had the opportunity to ask MacEachern some questions about his entrepreneurial journey (so far) with GestureLogic:

What’s the hardest thing about building a high tech business in Ottawa?

It’s certainly possible to build a high-tech business in Ottawa. The proof of that is in the many successful high-tech businesses that have grown in Ottawa and even expanded outside of Ottawa.  What is hard to do in Ottawa is to build a business to consumer company. There aren’t many of those in Ottawa.  Especially, there aren’t many mass consumer oriented companies in Ottawa at present. It’s, therefore, often necessary to travel outside of Ottawa to find mentorship and advice when it comes to building a company that’s targeted towards the mass consumer.  The sales and marketing knowledge required to reach the mass consumer is generally not found in Ottawa, or even in Canada.

What’s the easiest thing about building a high tech business in Ottawa?

Initially we had some concerns over whether we could find the talent required to build GestureLogic in Ottawa and, by extension, Canada. For example, we needed a machine intelligence expert, an embedded code optimization expert, and so on. These skill sets are not that common.

As it turned out, Ottawa has no shortage of hardware and software engineers, and we have been able to recruit highly skilled personnel to fill all of our major technical positions. This is in part due to the existing infrastructure in Ottawa: excellent universities, local high-tech labs, and existing high tech enterprises already  in the city.

The Canadian government, in general, is helping with talent recruitment, through incentive programs, accelerators, and incubators.

What’s the biggest challenge you’ve faced while building GestureLogic?

The biggest challenge we face while building GestureLogic has been the constraint on resources, and in particular human resources. We would love to scale faster, but financial reality cannot be ignored. With a business to consumer play such as we are undertaking, we cannot take a slow growth path.

Consequently, securing investment on an on-going basis is a continual challenge. Validating the business model and market as a hardware start-up is difficult because we need to expend capital on prototyping.

What’s the real problem that GestureLogic is looking to solve?

Right now there are wearable activity trackers that are moving a lot of data to cloud servers.  This data is predominantly acquired from body-mounted accelerometers.  Consequently there is a limited amount of information available for online processing and data mining.

Since GestureLogic’s technology acquires true bio-signals from the body, we will have available a vast amount of crowd sourced fitness data on which to operate. The problem we are solving is how to effectively utilize this data in a meaningful way for the users of the system. What we are building is a “fitness intelligence”, which encompasses advanced monitoring capability, advanced user feedback, and adaptive learning, integrated into the information flow and processing portions of the entire system.

 

Exit mobile version